U.S. patent number 7,720,857 [Application Number 10/927,316] was granted by the patent office on 2010-05-18 for method and system for providing an invisible attractor in a predetermined sector, which attracts a subset of entities depending on an entity type.
This patent grant is currently assigned to SAP AG. Invention is credited to Joerg Beringer, Michael Hatscher, Horst Werner.
United States Patent |
7,720,857 |
Beringer , et al. |
May 18, 2010 |
Method and system for providing an invisible attractor in a
predetermined sector, which attracts a subset of entities depending
on an entity type
Abstract
A visualization graph is provided on a computer by storing data
corresponding to a plurality of entities having a particular type,
wherein a semantic net includes the entities and wherein the
entities are linked to each other by a plurality of relations. The
visualization graph is provided in response to a query with respect
to an entity selected from the plurality of entities, wherein the
visualization graph includes a plurality of sectors representing
the results of the query. Entities are allocated to a predetermined
sector of the graph depending on their entity type.
Inventors: |
Beringer; Joerg (Frankfurt,
DE), Hatscher; Michael (Osnabruck, DE),
Werner; Horst (Rettigheim, DE) |
Assignee: |
SAP AG (Walldorf,
DE)
|
Family
ID: |
34105748 |
Appl.
No.: |
10/927,316 |
Filed: |
August 27, 2004 |
Prior Publication Data
|
|
|
|
Document
Identifier |
Publication Date |
|
US 20050114384 A1 |
May 26, 2005 |
|
Foreign Application Priority Data
|
|
|
|
|
Aug 29, 2003 [EP] |
|
|
03077697 |
Nov 14, 2003 [EP] |
|
|
03078585 |
|
Current U.S.
Class: |
707/766; 717/125;
715/853; 707/798; 707/778; 345/676 |
Current CPC
Class: |
G06F
16/9038 (20190101) |
Current International
Class: |
G06F
17/30 (20060101); G06F 3/048 (20060101); G06F
9/44 (20060101); G09G 5/02 (20060101) |
Field of
Search: |
;345/672,427,440,676,679-681
;707/1-4,7,100,102,104.1,200,709-710,713,716,731,757-758,766,777-778,797-798,920,956
;715/273,700,713,762-763,853-854,779 ;717/105,125 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
1050829 |
|
Nov 2000 |
|
EP |
|
WO 92/11724 |
|
Jul 1992 |
|
WO |
|
WO 01/88751 |
|
Nov 2001 |
|
WO |
|
WO 02/069192 |
|
Sep 2002 |
|
WO |
|
WO 03/069506 |
|
Aug 2003 |
|
WO |
|
WO 2007/062885 |
|
Jun 2007 |
|
WO |
|
Other References
Fluit et al. ("Ontology-based Information Visualisation", Springer
Verlag, 2002, retrieved from
http://www.cs.vu.n1/.about.frankh/abstracts/VSW02.html, on Jan. 18,
2007). cited by examiner .
Nihar Sheth et al. "Visualizing MeSH Dataset using Radial Tree
Layout", Published on Apr. 29,2003, pp. 1-11. cited by examiner
.
Ming C Hao et al. [hereafter Ming], Web-based visualization of
large hierarchical graphs using invisible links in a Hyperbolic
space, HP Lab. published on Jan. 2000. cited by examiner .
Sonia Fernandes Silva et al. "Formalizing visual interaction withh
istorical databases", Information Systems 27 (2002) 487-521. cited
by examiner .
Edward PF Chan et al. "On multi-scale display of geometric
objects", Data and Knowledge Engineering, 40 (2002)91-119. cited by
examiner .
U.S. Appl. No. 10/927,313, filed Aug. 27, 2004, entitled "Methods
and Systems for Providing a Visualization Graph." cited by other
.
U.S. Appl. No. 10/927,315, filed Aug. 27, 2004, entitled "Methods
and Systems for Providing a Visualization Graph." cited by other
.
U.S. Appl. No. 10/927,458, filed Aug. 27, 2004, entitled "Methods
and Systems for Providing a Visualization Graph." cited by other
.
Herman et al., "Graph Visualization and Navigation in Information
Visualization: A Survey," IEEE, Jan.-Mar. 2000, pp. 24-43. cited by
other .
"Chapter 15: Topic Maps in Knowledge Organization," Jul. 16, 2002,
XML Topic Maps: Creating and Using Topic Maps for the Web, Addison
Wesley Professional, 43 pages. cited by other .
Baumgartner, Jason L., et al., "Roget2000: A 2D Hyperbolic Tree
Visualization of Roget's Thesaurus," SPIE Conference on
Visualization and Data Analysis, Jan. 2002, pp. 1-8. cited by other
.
Butler, Greg et al., "A Graph Database With Visual Queries for
Genomics," Proceedings Trim Size: 9.75 in x 6.5 in., Sep. 28, 2004,
10 pages. cited by other .
Communication from the EPO, dated Jan. 16, 2007 for European
Application No. 03 078 583.6-1225, 8 pages. cited by other .
Communication from the EPO, dated Jan. 17, 2007 for European
Application No. 03 078 584.4-1225, 8 pages. cited by other .
Communication from the EPO, dated Jan. 17, 2007 for European
Application No. 03 078 586.9-1225, 8 pages. cited by other .
Communication from the EPO, dated Jan. 19, 2009 for European
Application No. 03 078 583.6-2221, 9 pages. cited by other .
Communication from the EPO, dated Jan. 20, 2009 for European
Application No. 03 077 697.5-2221, 9 pages. cited by other .
Communication from the EPO, dated Jan. 20, 2009 for European
Application No. 03 078 584.4-2221, 10 pages. cited by other .
Communication from the EPO, dated Jan. 20, 2009 for European
Application No. 03 078 585.1-2221, 9 pages. cited by other .
Communication from the EPO, dated Jan. 20, 2009 for European
Application No. 03 078 586.9-2221, 9 pages. cited by other .
Communication from the EPO, dated Jul. 5, 2004 for European
Application No. 03 078 585.1-1225, 4 pages. cited by other .
Communication from the EPO, dated Nov. 8, 2006 for European
Application No. 03 078 585.1-1225, 9 pages. cited by other .
Communication from the EPO, dated Oct. 26, 2006 for European
Application No. 03 077 697.5-1225, 6 pages. cited by other .
Gansner, Emden R., et al., "An open graph visualization system and
its applications to software engineering," Prepared using
speauth.cls [Version: 1999/06/11 v1. 1a], Software-Practice and
Experience, 1999, pp. 1-29. cited by other .
Golovchinsky, G. et al., "Subverting structure: data-driven diagram
generation," Visualization, 1995, Visualization '95. Proceedings,
IEEE Conference in Atlanta, Georgia, Oct. 29-Nov. 3, 1995, Los
Alamitos, California, pp. 217-223. cited by other .
Groth, Dennis P., "Visual Representation of Database Queries Using
Structural Similarity," Proceedings of the Seventh International
Conference on Information Visualization (Iv'03), 2003, IEEE, 6
pages. cited by other .
Halin, Gilles, "An interactive graph visualization for handling
cooperative design activity context," The 11th International
Conference on CSCW in Design, Melbourne, Australia, 2007, pp. 1-5.
cited by other .
Huang, Mao Lin, "Information Visualization of Attributed Relational
Data," 2001, Australian Computer Society, Inc. This paper appeared
at the Australian Symposium on Information Visualization, Sydney,
Dec. 2001. Conferences in Research and Practice in Information
Technology, vol. 9, 7 pages. cited by other .
Hull, R. et al., "Semantic database modeling: survey, applications
and research issues," ACM Computing Surveys, ACM, New York, NY,
Sep. 1, 1987, pp. 201-260. cited by other .
Lamping, John et al., "A Focus + Context Technique Based on
Hyperbolic Geometry for Visualizing Large Hierarchies," Proceedings
of the ACM SIGCHI Conference on Human Factors in Computing Systems,
Denver, May 1995, ACM., pp. 1-8. cited by other .
Marshall, Scott, "Methods and Tools for the Visualization and
Navigation of Graphs," 2001, Universite Bordeau 1, Bordeaux,
France, 78 pages. cited by other .
Moreland, Kenneth et al., "Massive Graph Visualization: LDRD Final
Report," Oct. 2007, 48 pages. cited by other .
Mutton, Paul et al., "Visualization of Semantic Metadata and
Ontologies," Proceedings of the Seventh International Conference on
Information Visualization (IV'03), 2003, IEEE, 6 pages. cited by
other .
Nguyen, Quant Vinh, et al., "A space-optimized tree visualization,"
Information Visualization, 2002, INFOVIS 2002, IEEE Symposium, Oct.
28-29, 2002, 8 pages. cited by other .
Partial European Search Report for European Application No. 03 077
697.5-1225, dated Jun. 18, 2004, 5 pages. cited by other .
Staszak, C., "Semantic Network Picture Book," 2002, pp. 1-14. cited
by other .
Wills, Graham J., "NicheWorks--Interactive Visualization of Very
Large Graphs," 1999, pp. 190-212, XP007906624, Retrieved from the
Internet:
URL:http://www.amstat.org/Publications/jcgs/pdf99/wills.pdf>.
cited by other.
|
Primary Examiner: Channavajjala; Srirama
Attorney, Agent or Firm: Finnegan, Henderson, Farabow,
Garrett & Dunner, LLP
Claims
What is claimed is:
1. A method of providing a visualization graph on a computer with
memory, a processor, and a display device, the method comprising:
storing data in the memory corresponding to a plurality of entities
having a particular type, wherein a semantic net includes the
entities and wherein the entities are linked to each other by a
plurality of relations; providing, by executing a process in the
processor, a visualization graph on the display device in response
to a query with respect to an entity selected from the plurality of
entities, wherein the visualization graph includes: a first of the
entities, representing results of the query, displayed because it
is a focus entity defined by the user or the query a second of the
entities, representing the results of the query, displayed because
it is directly related to the focus entity, wherein a third of the
entities, representing the results of the query, is not displayed
because it is indirectly related to the focus entity; a fourth of
the entities, representing the results of the query, that is
indirectly related to the focus entity, wherein context information
is used to determine that the fourth entity be displayed; a
plurality of sectors representing the results of the query, the
plurality of sectors being subdivisions of a screen area with
boundaries; a plurality of sub-sectors being subdivisions inside
the boundaries of the plurality of sectors, the subsectors also
having boundaries, wherein a size of a predetermined one of the
plurality of sub-sectors depends on a number of the entities
allocated to the predetermined sub-sector, wherein a predetermined
one of the plurality of sectors has a size that depends on a number
of the entities allocated to the predetermined sector and the
number of the entities allocated to the predetermined sub-sector;
displaying the entities inside the boundaries of the predetermined
sector and the boundaries of the predetermined sub-sector of the
visualization graph depending on an entity type and entity sub-type
of the allocated entities, respectively; and providing an invisible
attractor in the predetermined sector, which attracts a subset of
the entities to the predetermined sector depending on the entity
type of the subset of entities, wherein the invisible attractor
remains invisible during user interaction with the visualization
graph.
2. The method according to claim 1, wherein if an additional entity
of a particular entity type is stored in the storing step, the
location on the graph of the allocated entities is adapted in
accordance with the additional entity.
3. The method according to claim 1, comprising: providing repulsors
to repulse the entities allocated to the predetermined sector from
one another.
4. The method according to claim 1, wherein the location of an
entity on the graph is determined by a sum of the influence exerted
on the entity by the attractor and the repulsors.
5. The method according to claim 1, comprising: reallocating the
plurality of sectors and the plurality of sub-sectors in the
visualization graph if the number of entities to be displayed on
the graph changes.
6. The method according to claim 1, comprising: selecting entities
from the plurality of entities having at least one common relation
and storing the selected entities as a plurality of groups;
representing the groups on the graph as a plurality of nodes; and
representing only the relations which all of the nodes share in
common.
7. The method according to claim 6, wherein the selecting step
includes abstracting the relations to find the common relation.
8. The method according to claim 1, comprising: representing a
plurality of entities having a common relation as a first node on
the visualization graph; causing the entities comprised at the
first node to be displayed in response to a predetermined stimulus;
and causing the graph to restructure so that the entities displayed
are replaced by the node in response to a further predetermined
stimulus.
9. The method according to claim 8, wherein in response to the
first predetermined stimulus, the node remains in the graph to
represent the common relation.
10. The method according to claim 8, wherein the entities are
linked to a further entity or node via a link which represents a
relation that is not common to all entities linked to the first
node.
11. The method according to claim 1, wherein a distance of the
entities from a center of the visualization graph is an oscillating
function of an angle of the predetermined sector in order to avoid
collisions.
12. A computer for providing a visualization graph, the computer
comprising: a storage medium having recorded therein processor
readable code processable to provide a visualization graph; a
database for storing data corresponding to a plurality of entities
having a particular type, wherein a semantic net includes the
entities and wherein the entities are linked to each other by a
plurality of relations; a query interface adapted, so that in
response to a query with respect to an entity selected from the
plurality of entities, a visualization graph is provided
representing the results of the query, wherein the code comprises
an allocator code processable to: allocate a first of the entities,
representing results of the query, displayed because it is a focus
entity defined by the user or the query; allocate a second of the
entities, representing the results of the query, displayed because
it is directly related to the focus entity, wherein a third of the
entities, representing the results of the query, is not displayed
because it is indirectly related to the focus entity; allocate a
fourth of the entities, representing the results of the query, that
is indirectly related to the focus entity, wherein context
information is used to determine that the fourth entity be
displayed; allocate a first set of the entities to a predetermined
sector of the graph depending on an entity type, the predetermined
sectors being subdivisions of a screen area with boundaries;
allocate a second set of the entities to a predetermined sub-sector
being a subdivision inside the boundaries of the predetermined
sector depending on an entity sub-type, the sub-sectors also having
boundaries, wherein a size of the predetermined sub-sector depends
on a number of the second set of entities allocated to the
predetermined sub-sector, wherein the predetermined sector has a
size that depends on a number of the first set of the entities
allocated to the predetermined sector and the number of the second
set of the entities allocated to the predetermined sub-sector; and
provide an invisible attractor in the predetermined sector, which
attracts a subset of the entities to the predetermined sector
depending on the entity type of the subset of entities, wherein the
invisible attractor remains invisible during user interaction with
the visualization graph.
13. The computer according to claim 12, wherein if an additional
entity of a particular entity type is stored in the storing step,
the location on the graph of the allocated entities is adapted in
accordance with the additional entity.
14. The computer according to claim 12, wherein the allocator code
comprises a plurality of repulsor codes processable to repulse the
entities allocated to the predetermined sector from one
another.
15. The computer according to claim 12, wherein the location of an
entity on the graph is determined by a sum of the influence exerted
on the entity by the attractor code and the repulsor codes.
16. The computer according to claim 12, wherein the allocator code
comprises repeater code processable to reallocate the plurality of
sectors and the plurality of sub-sectors in the visualization graph
if the number of entities to be displayed on the graph changes.
17. The computer according to claim 12, wherein the code further
comprises selection code processable to select entities from the
plurality of entities having a common relation and storing the
selected entities as a plurality of groups and representation code
processable to represent the groups on the graph as a plurality of
nodes, wherein only relations for which all of the nodes share in
common are represented.
18. The computer according to claim 12, wherein the code further
comprises representation code processable to represent a plurality
of entities having a common relation as a node on the visualization
graph, and in response to a predetermined stimulus causes the
entities comprised at the node to be displayed, and in response to
a further predetermined stimulus causes the graph to restructure so
that the entities displayed are replaced by the node.
19. The computer according to claim 12, wherein a distance of the
entities from a center of the visualization graph is an oscillating
function of an angle of the predetermined sector in order to avoid
collisions.
20. A program storage device readable by a processing apparatus,
the device embodying instructions executable by the processor to
perform the steps of: storing data corresponding to a plurality of
entities having a particular type, wherein a semantic net includes
the entities and wherein the entities are linked to each other by a
plurality of relations; providing a visualization graph in response
to a query with respect to an entity selected from the plurality of
entities, wherein the visualization graph includes: a first of the
entities, representing results of the query, displayed because it
is a focus entity defined by the user or the query; a second of the
entities, representing the results of the query, displayed because
it is directly related to the focus entity, wherein a third of the
entities, representing the results of the query, is not displayed
because it is indirectly related to the focus entity; a fourth of
the entities, representing the results of the query, that is
indirectly related to the focus entity, wherein context information
is used to determine that the fourth entity be displayed; a
plurality of sectors representing the results of the query, the
plurality of sectors being subdivisions of a screen area with
boundaries; a plurality of sub-sectors being subdivisions inside
the boundaries of the plurality of sectors, wherein a size of a
predetermined one of the plurality of sub-sectors depends on a
number of the entities allocated to the predetermined sub-sector,
wherein a predetermined one of the plurality of sectors has a size
that depends on a number of the entities allocated to the
predetermined sector and the number of the entities allocated to
the predetermined sub-sector; displaying the entities inside the
boundaries of the predetermined sector and boundaries of the
predetermined sub-sector of the visualization graph depending on an
entity type and entity sub-type of the allocated entities,
respectively; and providing an invisible attractor in the
predetermined sector, which attracts a subset of the entities to
the predetermined sector depending on the entity type of the subset
of entities, wherein the invisible attractor remains invisible
during user interaction with the visualization graph.
Description
This application is based upon and claims the benefit of priority
from prior patent application EP 03077697.5, filed Aug. 29, 2003,
and prior patent application EP 03078585.1, filed Nov. 14, 2003,
the entire contents of each which are expressly incorporated herein
by reference.
BACKGROUND
I. Technical Field
The present invention relates to a methods and systems for
providing a visualization graph on a computer.
II. Background Information
Visualization graphs are tools that allow data to be handled and
displayed on a display device according to certain criteria. The
primary objective of navigation graphs is to display systems of
complex interrelationships between entities, such as in a database
or on the World Wide Web. Visualization graphs can be based on a
semantic net including all entity types that occur where the
considered entities are linked to each other by various kinds of
relations. A visualization graph represents entities as boxes,
often referred to as "nodes" of the graph, and relations as lines
between the boxes.
A common way of solving the problem of graphical layout is to apply
a physical simulation where all entities are treated as masses
repulsing each other and the relations are treated as elastic lines
trying to pull connected entities together. By double-clicking on a
box, other entities that are directly related to the corresponding
entity (but which may not yet in the graph) and their relations to
other entities in the graph are included. In some implementations
the double-clicked entity then moves to the center of the graph (it
becomes the "focus" entity) and other nodes, which are too distant
(measured in number of relations on the shortest path) from it are
removed from the graph.
However, conventional visualization graphs suffer drawbacks. One
problem with conventional visualization graphs using a
non-deterministic approach is that entities are arranged in a
random. Thus, the orientation within the graph is not optimal.
SUMMARY
Consistent with the present invention, a method of providing a
visualization graph on a computer comprises storing data
corresponding to a plurality of entities having a particular type,
wherein a semantic net includes the entities and wherein the
entities are linked to each other by a plurality of relations; in
response to a query with respect to an entity selected from the
plurality of entities, providing a visualization graph having a
plurality of sectors representing the results of the query; and
allocating the entities to a predetermined sector of the graph
depending on their entity type. By allocating entities to a
predetermined sector of the graph depending on their entity type,
the location of the entity types can be predicted.
Consistent with the present invention, a computer for providing a
visualization graph comprises a storage medium having recorded
therein processor readable code processable to provide a
visualization graph; a database for storing data corresponding to a
plurality of entities having a particular type, wherein a semantic
net includes the entities and wherein the entities are linked to
each other by a plurality of relations; a query interface adapted,
so that in response to a query with respect to an entity selected
from the plurality of entities, a visualization graph is provided
representing the results of the query, wherein the code comprises a
plurality of attractor codes processable to attract the entities to
a predetermined sector of the graph depending on their entity
type.
It is to be understood that both the foregoing general description
and the following detailed description are exemplary and
explanatory only, and should not be considered restrictive of the
scope of the invention, as described and claimed. Further, features
and/or variations may be provided in addition to those set forth
herein. For example, embodiments of the invention may be directed
to various combinations and sub-combinations of the features
described in the detailed description.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are incorporated in and constitute
a part of this disclosure, illustrate various embodiments and
aspects of the present invention. In the drawings:
FIG. 1 shows a grouping in a visualization graph;
FIG. 2 shows further details of the visualization graph shown in
FIG. 1;
FIGS. 3-6 show visualization graphs according to embodiments of the
present invention;
FIG. 7 shows a visualization graph according to a further
embodiment of the present invention;
FIG. 8 shows further details of the visualization graph shown in
FIG. 7; and
FIG. 9 shows an exemplary computer for carrying out the methods
according to embodiments of the invention.
DETAILED DESCRIPTION
The following detailed description refers to the accompanying
drawings. Wherever possible, the same reference numbers are used in
the drawings and the following description to refer to the same or
similar parts. While several exemplary embodiments and features of
the invention are described herein, modifications, adaptations and
other implementations are possible, without departing from the
spirit and scope of the invention. For example, substitutions,
additions or modifications may be made to the components
illustrated in the drawings, and the exemplary methods described
herein may be modified by substituting, reordering or adding steps
to the disclosed methods. Accordingly, the following detailed
description does not limit the invention. Instead, the proper scope
of the invention is defined by the appended claims.
FIGS. 1 and 2 show examples of embodiments of the present
invention. In particular, FIG. 1 shows the position of attractors
for top-level entity types, also referred to as "types" and FIG. 2
shows the approximate position of attractors for second-level
entity types, also referred to as "sub-types." FIG. 1 shows details
of a visualization graph 1 wherein a plurality of entities 2 are
displayed. Associated with each entity is an attractor 3. The
attractors do not appear on the graph to a user, but are
schematically depicted as dotted circles 3.
The entities 2 are typically modelled as a mass. There is a
repulsive force exerted by a repulsor between each pair of
entities. The repulsive force may be inversely proportional to the
distance or the square of the distance, or any other inverse
relationship. The relations between entities (not shown in FIG. 1)
are modelled as springs, typically linear springs. The model
provides damping to ensure that the system converges. When energy
is put into the system, for example, when entities 2 are introduced
into the graph or moved, the system is modelled to adopt the lowest
energy level. For each entity or node (refer to FIG. 3), the
distance and repulsive force is calculated from other entities and
nodes. The forces are added to obtain a force vector. The reaction
of the system in terms of acceleration and deceleration is
dependent on the force vector. To facilitate orientation, certain
types (or kinds) of entities 2 are arranged to appear in the same
sector 4 of the graph 1.
A first embodiment is based on a non-deterministic approach, using
attractors and repulsors. A second embodiment is based on a
deterministic approach using a dynamic, but deterministic,
subdivision of the screen and screen areas into sectors and
sub-sectors, wherein entity types are allocated to sectors and
entity sub-types are allocated to sub-sectors, respectively.
The first non-deterministic embodiment is now described. To
facilitate orientation certain kinds, that is types, of entities 2
are arranged to appear in the same sector 4 of the graph. Invisible
attractors 3 that are not visible to a user of the graph are
introduced for each entity type. In the example, shown in FIG. 1
the types are "attribute," "knowledge," "property," "real world
object," and "activity". These may be referred to as top-level
entity types. The angle theta 1-theta 4 of each attractor 3 with
respect to a reference may be set by customizing and is inherited
by all subtypes (refer to FIG. 2 which depicts subtypes 6, wherein
subtypes are entities 2 which have a type falling within the scope
of a top-level type. For example, in FIG. 2 "strategic business
planning" is a sub-type of "activity."
It is seen in FIGS. 1 and 2 that within each sector 4, 7 the
entities to be placed are arranged in FIG. 1 in an ellipse, whereas
in FIG. 2, because there are more entities to be arranged, and thus
force vectors are more complex, in each sector 4, the sub-type
entities, rather than being arranged in an ellipse are arranged in
a more nebulous arrangement. Further, because the force vectors are
more complex in FIG. 2, where a large number of entities are
located in a relatively small area, the location of each entity
does not correspond exactly to the location of its respective
attractor, because the repulsive forces between entities also play
a role in the location of the entity. Thus, FIG. 2 shows the
approximate location of the attractors 3 as dotted lines.
It will be understood that the negotiation of sector size
determined in accordance with the number of entities and how they
are to be distributed causes the graph to have a particular
fuzziness. As mentioned, this is achieved by the provision of the
attractors 3. In contrast, in conventional graphs, there is no
flexibility in the system to expand or contract a sector beyond or
within its boundary, respectively, should the need arise when
entities are either added or taken away from the sector.
The second deterministic embodiment is now described. The principle
of the present invention may also be used to arrange nodes (refer
to FIG. 2) in a navigation graph without the use of repulsors
and/or attractors. According to an embodiment of the present
invention, the following steps are carried out: the display, which
is typically a computer screen, is divided into sectors 4 assigned
to the respective top-level entity types 2. The size of each sector
depends on the number of entities or nodes it contains, including
all visible subtypes 6. For example, if a larger number of entities
are to be placed in a particular sector, that sector will become
larger. Then the sectors are recursively divided into subtype
sectors 7 and again, their relative size depends on the number of
entities they contain. The segmentation of the screen is repeated
each time that entities are added to or removed from the graph 1.
The distance of the entities or nodes to the center of the graph is
an oscillating function of the angle in order to avoid collisions
(which in the simulative approach are avoided by the repulsive
force between entities). It will be understood that whilst the
first and second embodiments may be alternatively implemented, a
combination of the first and second embodiments may also be
implemented.
In one embodiment, if an additional entity of a particular entity
type is stored in the storing step, the location on the graph of
the allocated entities is adapted in accordance with the additional
entity. In this way, the graph becomes dynamic and more
versatile.
The method may include the further step of providing attractors 3
which attract the entities to the predetermined sector in
accordance with their entity types. In doing so, a so-called
"360.degree. Navigation Graph" is achieved, whereby the location of
each entity can be predicted without having to carry out a
complete, and thus, very complex deterministic approach.
Further, the method may include the further step of providing
repulsors to repulse the entities allocated to the predetermined
sector 4 from one another. This achieves an optimization of the
distribution of entities 2 within a sector 4. Further, the location
of an entity 2 on the graph 1 may be determined by the sum of the
influence exerted on the entity 2 by the attractor 3 and the
repulsors.
In a further embodiment, the method may include the steps of:
dividing the graph into sectors 4, wherein an entity 2 is allocated
to one of the sectors 4 according to its entity type, and dividing
the sectors 4 into sub-sectors 7, wherein an entity 2 is allocated
to one of the sub-sectors 7 in accordance with its entity sub-type,
wherein the size of the sectors 4 and the sub-sectors 7 is
determined in accordance with the number of entities of a
particular type allocated to the sector 4 and the number of
entities of a particular sub-type allocated to the sub-sector 7,
respectively. By doing this, a deterministic approach is realized
without the complexity of conventional deterministic
approaches.
In a yet further embodiment, the method may include the step of:
repeating the dividing steps if the number of entities 2 to be
displayed on the graph 1 changes. By doing so, a dynamic
deterministic approach is realized, which is adaptive and
versatile.
FIG. 3 shows a visualization graph according to further embodiments
of the present invention. In particular, FIG. 3 shows a focus
entity 10 with related entities 2 and those comprised in nodes 9,
clustered by entity type. The dashed lines indicate indirectly
related items, "competitors", "market", selected due to user
preferences.
FIG. 4 shows further details of the visualization graph shown in
FIG. 3. In particular, FIG. 4 depicts a display of a group's common
relations 8 as indicated when a mouse, or other indicator adapted
for use with a computer, is passed over the desired node
(MouseOver).
As shown in FIGS. 3 and 4, to avoid a visualization graph 1 getting
crowded and the data complex to navigate as a result, groups of
entities 9 with common relations 8 are bundled and displayed as
group nodes 9 (FIG. 3). Of all possible groupings those are
selected which result in the most even distribution of entities 2
(also referred as elements) over the groups and which form groups
of entities 2 (elements) which have at least two relations 8 in
common.
The common relations 8 may be explicitly assigned to each entity in
a group, but they may also be abstractions of the individual
relations 8. This embodiment is shown in FIG. 4, where the common
relations 8 of the group "sanitary napkins" are displayed: each of
these products has got a relation 8 "refers to German market" and a
relation 8 "has property biodegradability." These are direct
relations 8. For example, a company having access to the graph
sells two products in the group and competing companies sell the
remaining products. Since the semantic net contains the information
that all those are companies, a common abstract relation 8 "is sold
by some company" is created, which also characterizes the elements
of the group.
The selection code is dynamic resulting in a dynamic grouping of
the entities. That is, depending on certain criteria such as the
context, the selection and abstraction, if applied, may at
different times provide different groupings. In a preferred
embodiment, the method comprises the further step of selecting
those entities from the plurality of entities having at least one
common relation 8 and storing the selected entities as a plurality
of groups, representing the groups on the graph as a plurality of
nodes 9, and representing only those relations 8 which all of the
nodes 9 have in common. By grouping of entities with common
relations 8 and displaying the group as one node 9 (represented as
an ellipse rather than a box in FIGS. 3 and 4) in the graph, and by
providing lines representing only the relations 8 that all nodes in
the graph have in common, an efficient representation of the
entities and an efficient use of the graph is achieved. Further,
characteristics are used to identify common relations 8 in such a
way that a good distribution of nodes 9 is achieved.
In a preferred embodiment, a selecting step includes abstracting
the relations 8 to find the common relation 8. By abstracting the
relations 8, characteristics are used to identify common relations
8. In such a way that an even distribution of nodes in the graph is
achieved.
In a further embodiment, to further improve the predictability of
the selection, facets are introduced. In particular, in order to
increase the predictability with regard to what common relation 8
will be chosen as criterion to form groups, the user may define
facets for each entity type. Facets are predefined groups that are
characterized by the entity type of their elements or the kind of
relation 8 that connects their elements to the focus entity.
In the example, the following facets have been defined for product
properties knowledge, products, technologies, persons, life cycle
phases, companies, ideas, insights, facts, concepts, approaches,
activities. If facets are defined, all entities related to the
focus entity will be sorted into the corresponding facets (groups)
and the dynamic grouping algorithm is used only to subdivide these
facets into smaller groups (if possible).
FIGS. 5-8 show visualization graphs according to examples of
further embodiments of the present invention. In particular, FIG. 5
depicts an exploding group 15, wherein association of members to
group remains visible. FIG. 6 depicts a display of entity type 16
as viewed with the MouseOver function. FIG. 7 depicts an explosion
of a group into subgroups 17. FIG. 8 depicts the explosion of a
subgroup 18.
As mentioned, in contrast to conventional visualization graphs, an
aspect of the present invention allows the formation of groups in a
2D visualization graph whilst keeping it clear. According to an
embodiment of the present invention this is achieved by keeping the
space required for the nodes minimal and the origin of the added
nodes traceable. Further, the graph is rearranged in a smooth way
to avoid confusion of the user.
According to an embodiment of the invention, the following steps
are taken. Before exploding, the group node increases repulsive
force proportionally to the number of entities to be inserted in
order to make room for the new nodes. The actual insertion begins,
when the neighbor nodes have moved sufficiently far away. Although
the new nodes inserted into to the graph have a direct relation 8
to the "focus" node 10, this relation 8 is only displayed
indirectly: the new entities are connected to the group node which
remains in the graph as "bundler" without label and establishes the
relation 8 to the "focus" node 10. Thus the number of lines
connected to the center node 10 remains low.
While a group "bundler" node 11 doesn't have a label in order to
save space, the group's characteristics are shown when the user
moves the mouse pointer over the "bundler" node 11, in the same way
as shown in FIG. 4.
Double-clicking a "bundler" node 11 causes group to collapse again
into one node. The recursive explosion and collapsing of subgroups
18 is also possible (FIG. 7,8). The resulting representation looks
and behaves similar to a "tree view control". The main difference
is that a tree view represents an existing hierarchical structure,
whereas the group nodes in the graph dynamically create a
hierarchy-like structure in order to get a clearer graph layout.
Also the problem of finding a 2D graph layout does not exist for
conventional tree view controls.
In a particular embodiment, the method may include step of:
representing a plurality of entities 2 having a common relation 8
as a first node 9 on the visualization graph 1, and in response to
a predetermined stimulus causing the entities 2 comprised at the
first node 9 to be displayed, and in response to a further
predetermined stimulus causing the graph to restructure so that the
entities displayed are replaced by the node 9. By providing the
possibility to explode such groups (i.e. to display all group
entities as separate nodes in the graph) by double-clicking and to
put them back into the group again, links between nodes
representing relations 8 are kept to a minimum which optimizes the
energy in the graph. Further, it becomes easier for the user to
orientate within the graph, thus, improving his navigation of the
information represented in the graph.
In a preferred embodiment, in response to the first predetermined
stimulus, the node 9 remains in the graph to represent the common
relation 8. As a result even in the "exploded" state, the "group
node" is kept in the graph and represents the common relations 8,
while the single group members (entities) have a link to the group
node. Further, the entities may be linked to a further entity or
node via a link which represents a relation 8 which may not be
common to all entities linked to the first node 9. By providing
links that may not be common to all members of the group (linked by
a common relation 8 to the first node), the user has access to
further navigable information.
As mentioned, in contrast to conventional visualization graphs,
certain embodiments of the present invention provide a
visualization graph layout such that the number of nodes is kept
low without missing out potentially relevant information.
According to an embodiment of the present invention this is
achieved in the following way: when the focus of a graph changes,
new related entities are inserted, and therefore other entities
have to be removed. In conventional visualization graphs, only
nodes in the graph are kept which have a distance d<d.sub.max
from the focus node, where the distance is the number of relations
8 on the shortest path between a node and the focus node. Since the
number of nodes usually increases exponentially with d.sub.max, a
value of 1 or 2 is appropriate for most purposes.
To enhance navigation of the visualization graph, entities of
certain types may be included in the graph even if they are far
more distant to the focus, if they are considered to be of special
interest in the current context either due to their entity type or
due to the kind of relations 8 linking them to the focus node.
The context information in this case can be made up, but is not
limited, from the following components current user's general
preferences, context information attached to the "focus" node, and
current user's current role and/or session history. In FIGS. 3 to
8, the entity 2 "German market" and a group of "four competitors"
12 appear in the graph connected with dashed lines to the focus
node 10. These entities 12 have no direct relation 8 to the product
property "biodegradability," but are related via some products. In
this case, the system has been told that if an entity of the type
"product property" is in the focus, markets and competitors are of
special interest. So all markets and competitors in a certain
distance d<4 to the entity "biodegradability" are selected and
inserted into the graph. More sophisticated algorithms may be
applied to find entities of special interest and it is even
possible to let the user create context specific algorithms by
means of a scripting language or macro recorder.
According to a particular embodiment, the method may comprise the
further steps of: storing 24 data corresponding to a plurality of
entities and/or nodes 2, 9, wherein a semantic net includes the
entities and/or nodes 2, 9 and wherein the entities and/or nodes 2,
9 are linked to each other by a plurality of relations 8,
generating a query, performing the query on the data, and
outputting at least two of the plurality of data in the form of a
visualization graph 1 representing the results of the query,
wherein the graph 1 has a focus entity or node 10 defined by a user
or the query, and using context information to determine at least
one entity and/or node to be output in the results which is
indirectly related to the focus 10.
By providing the possibility to display entities that are
indirectly related to the "focus" entity based on the current
context and user preferences, the user is able to collect
additional information even if there is no direct relationship
between entities. Thus, allowing the user to "jump" from context to
context within the graph. This embodiment of the present invention
allows a user to find how large amounts of data are related. The
user is able to navigate and explore knowledge domains in a visual
way.
FIG. 9 shows a typical computer arrangement for carrying out the
methods according to embodiments of the invention. In particular,
FIG. 5 shows a computer 20 including a central processing unit
(CPU) 22. The computer further includes a storage medium, which may
be located in the CPU 22 and/or elsewhere. In the storage medium
processor readable code is stored, which may be read by the CPU 22
to provide a visualization graph. Various codes may be stored an
allocator code processable to allocate the entities to a
predetermined sector of the graph depending on their entity type,
additional entity allocator code processable so that if an
additional entity of a particular entity type is stored in a
storing step, the location on the graph of the allocated entities
is adapted in accordance with the additional entity. The allocator
code may include a plurality of attractor codes processable to
attract the entities to a predetermined sector of the graph
depending on their entity type, respectively, a plurality of
repulsor codes processable to repulse the entities allocated to the
predetermined sector from one another. The attractor codes and the
repulsor codes are processable so that the location of an entity on
a graph is determined by the sum of the influence exerted on the
entity by the attractor code and the repulsor codes.
The allocator code may further comprise dividing code processable
to divide the graph into sectors, wherein an entity is allocated to
one of the sectors according to its entity type, and further
dividing code processable to further divide the sectors into
sub-sectors, wherein an entity is allocated to one of the
sub-sectors in accordance with its entity sub-type, wherein the
size of the sectors and the sub-sectors is determined in accordance
with the number of entities of a particular type allocated to the
sector and the number of entities of a particular sub-type
allocated to the sub-sector, respectively.
The allocator code may also include repeater code processable to
activate the dividing code if the number of entities to be
displayed on a graph changes. The processable code may further
comprise selection code processable to select those entities from
the plurality of entities having a common relation 8 and storing
the selected entities as a plurality of groups, representation code
processable to represent the groups on the graph as a plurality of
nodes, wherein only those relations 8 which all of the nodes have
in common are represented.
In further embodiments of the present invention, the code may also
include representation code processable to represent a plurality of
entities having a common relation 8 as a node on a visualization
graph, and in response to a predetermined stimulus causing the
entities comprised at the node to be displayed, and in response to
a further predetermined stimulus causing a graph to restructure so
that the entities displayed are replaced by the node. Also provided
is a display device 30, such as a screen, for displaying a
visualization graph 1.
The user may use a keyboard 40, mouse 42 or other operating device
to communicate with the computer 20 and to instruct the computer to
perform a query. The query may be generated automatically or by a
user. Context information may be defined in the query.
Alternatively, it may not form part of the query, and may be
defined in some other way, for example, by user preferences.
In one embodiment, a computer 20 is provided for providing a
visualization graph 1, the computer 20 may comprise: a database 24,
60 for storing data corresponding to a plurality of entities and/or
nodes 2, 9, wherein a semantic net includes the entities and/or
nodes 2, 9 and wherein the entities and/or nodes 2, 9 are linked to
each other by a plurality of relations 8, a storage medium 22
having recorded therein processor readable code processable to
provide a visualization graph 1, the code including a query code
processable to perform a query on the database, an output device 30
for outputting at least two of the plurality of data in the form of
a visualization graph 1 representing the results of the query,
wherein the graph 1 has a focus entity or node 10 defined by a user
or the query, wherein the code further includes context code
processable to express context information which is processable to
determine at least one entity and/or node to be output in the
results which is indirectly related to the focus 10.
Further, the context code may be processable to allow at least one
entity 2 and/or node 9 to be output in the results that are
indirectly related by more than two relations 8. The context code
may also be processable to enable identification of at least one
entity and/or node 2, 9 having a particular interest with respect
to the focus 10, and/or may be processable to identify a particular
interest on the basis of an entity 2 or node 9 type or due to the
relations 8 linking the entity and/or node 2, 9 to the focus 10.
Further, the context code may be determined by any or a combination
of: at least one predetermined user preference, information
associated with the focus, or a user's current role and/or session
history query.
In one embodiment, the database 24 in which data for building the
graph is stored, may be located locally at the computer 20.
Alternatively or in addition, the database 60 or an additional
database may be located remotely from the computer 20. In such an
embodiment, the computer is provided with means to remotely access
a remote database. For example, using a modem 26 connected via the
Internet 50 or other network or communications link to the remote
database 60. Although the embodiment shown in FIG. 9 is a typical
Internet configuration, other configurations may also be possible.
As mentioned, a stand-alone configuration is also envisaged.
Further, the database may be distributed over more than one
computer. While parts of the processing may be performed on the
user's computer, other parts of the processing may be performed
remotely at a remote computer.
In the embodiments of the present invention described above, the
visualization graph is concerned with aspects of company dealing
with personal hygiene products. However, the invention is not
limited in this respect. The present invention finds application in
any sphere where data is to be navigated. In particular, where
complex interrelationships of data are to be navigated. Further
applications are found where data in one or more databases is
somehow related to one another. Further applications include
Internet applications, where metadata is accessed and used. The
expression "visualization graph" is intended to cover visual
representations, such as navigation graphs and other such
tools.
While certain features and embodiments of the invention have been
described, other embodiments of the invention will be apparent to
those skilled in the art from consideration of the specification
and practice of the embodiments of the invention disclosed herein.
Furthermore, although embodiments of the present invention have
been described as being associated with data stored in memory and
other storage mediums, one skilled in the art will appreciate that
these aspects can also be stored on or read from other types of
computer-readable media, such as secondary storage devices, like
hard disks, floppy disks, or a CD-ROM, or other forms of RAM or
ROM. Further, the steps of the disclosed methods may be modified in
any manner, including by reordering steps and/or inserting or
deleting steps, without departing from the principles of the
invention.
It is intended, therefore, that the specification and examples be
considered as exemplary only, with a true scope and spirit of the
invention being indicated by the following claims and their full
scope of equivalents.
* * * * *
References